Supplier Evaluation and Selection System of Embedded E-Commerce Platform Based on Big Data

Pub Date : 2022-04-01 DOI:10.4018/ijisscm.287629
Jiangnan He, Y. Qian, Xiaoyin Yin
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Abstract

For e-commerce companies, it is easier to obtain a large amount of aggregated data about user behavior with the help of embedded network platforms, which contains valuable information that helps to form effective decision-making. This article first gives a detailed introduction to the evaluation and selection of e-commerce and suppliers; then puts forward the analytic hierarchy process and entropy method; finally, the AHP analytic method is used to build a supplier evaluation system and a selection system. The experimental results of this paper show that after obtaining the entropy AHP weights through the analytic hierarchy process, these 8 suppliers can be ranked and selected. Using the ABC classification method, classification is based on the ranking of suppliers. Among them, Class A suppliers account for 12.5%, which plays a key role in the construction of the evaluation and selection system of e-commerce suppliers.
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基于大数据的嵌入式电子商务平台供应商评价与选择系统
对于电子商务公司来说,借助嵌入式网络平台更容易获得大量的用户行为汇总数据,这些数据中包含有价值的信息,有助于形成有效的决策。本文首先详细介绍了电子商务与供应商的评价与选择;然后提出了层次分析法和熵法;最后,运用层次分析法构建了供应商评价体系和选择体系。本文的实验结果表明,通过层次分析法获得熵AHP权重后,可以对这8家供应商进行排序和选择。采用ABC分类法,根据供应商的排名进行分类。其中,A类供应商占12.5%,在电子商务供应商评价选择体系建设中起着关键作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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